| --- |
| library_name: kernels |
| license: apache-2.0 |
| tags: |
| - kernel |
| - webgpu |
| - wgsl |
| --- |
| # com.microsoft.GemmFastGelu |
|
|
| `com.microsoft` · ONNX Runtime contrib operator · contrib since_version 1 |
| |
| ## Description |
| |
| Fuses MatMul, an optional bias, and FastGelu: `Y = FastGelu(X @ W + bias)`. `X` has rank at least 2 with shape `(..., K)`, `W` has shape `(K, N)`, and `bias` has shape `(N)`. The activation runs in the float32 accumulator before the output is narrowed, avoiding an intermediate `(..., N)` tensor. Bfloat16 is not implemented. |
| |
| See the [ONNX Runtime `GemmFastGelu` contrib-operator spec](https://github.com/microsoft/onnxruntime/blob/main/docs/ContribOperators.md#com.microsoft.GemmFastGelu) for the reference semantics. |
| |
| ## Inputs |
| |
| | Name | Bind key | Logical dtype | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | |
| | `X` | `X` | `T` | — | — | Left operand of rank 2 or greater with shape `(..., K)`; every leading-axis coordinate identifies a row of the product. | required | |
| | `W` | `W` | `T` | `2` | — | Right operand with shape `(K, N)`. | required | |
| | `bias` | `bias` | `T` | `1` | — | Optional bias with shape `(N)`, added before the activation. | optional | |
| |
| ## Outputs |
| |
| | Name | Bind key | Logical dtype | Rank | Shape | Description | Presence | |
| | --- | --- | --- | --- | --- | --- | --- | |
| | `Y` | `Y` | `T` | same as `X` | ONNX MatMul result of `X` and `W` | `FastGelu(X @ W + bias)`, with the same rank and leading dimensions as `X` and a trailing `N`. | required | |
| |
| ## Type constraints |
| |
| | Variable | Allowed dtypes | |
| | --- | --- | |
| | `T` | `float32`, `float16` | |
| |
| ## Device requirements |
| |
| Some implementation variants require `subgroup-matrix` and `subgroups`. These are route-specific capabilities, not package-wide requirements; availability also depends on the request shape and dtype. |
| |
| ## Files |
| |
| - [`metadata.json`](build/webgpu/metadata.json) — kernel metadata (id, digests, provenance) |
| - [`manifest.json`](build/webgpu/manifest.json) — the op contract (source of truth) |
| - [`test.json`](build/webgpu/test.json) — correctness cases |
| - [`bench.json`](build/webgpu/bench.json) — benchmark + tuning cases |
| - [`gemm-fast-gelu.wgsl.jinja`](build/webgpu/gemm-fast-gelu.wgsl.jinja) |
| - [`gemm-subgroup-matrix.wgsl.jinja`](build/webgpu/gemm-subgroup-matrix.wgsl.jinja) |
| |
| ## Use with `@huggingface/kernels` |
| |
| The loader derives every required output's shape and logical dtype from the manifest contract and this call. |
| It then allocates the result tensors automatically. |
| |
| The `version: 1` option selects the published kernel contract; it is independent of any operator opset, contrib `since_version`, or model version. |
|
|
| Replace each `*Data` placeholder with a typed array containing the corresponding input data. |
|
|
| ```js |
| import { getKernel } from "@huggingface/kernels"; |
| |
| const kernel = await getKernel("webgpu-kernels/com.microsoft.GemmFastGelu", { version: 1 }); |
| const { Y } = await kernel({ X: { data: XData, shape: [5, 6] }, W: { data: WData, shape: [6, 4] } }); |
| ``` |
|
|
